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Recent development of WRFDA the WRF Data Assimilation system Hans Huang, NCAR

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... development of WRFDA - the WRF Data Assimilation system. Hans Huang, NCAR. Acknowledge: NCAR/ESSL/MMM/DAG, NCAR/RAL/JNT/DATC, AFWA, USWRP, NSF-OPP, NASA, AirDat, ... – PowerPoint PPT presentation

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Title: Recent development of WRFDA the WRF Data Assimilation system Hans Huang, NCAR


1
Recent development of WRFDA- the WRF Data
Assimilation systemHans Huang, NCAR
Acknowledge NCAR/ESSL/MMM/DAG,
NCAR/RAL/JNT/DATC, AFWA, USWRP, NSF-OPP, NASA,
AirDat, KMA, CWB, CAA, BMB, EUMETSAT April 2009
2
Outline
  • WRFDA overview
  • A few new capabilities
  • 4D-Var (optimization and public release)
  • Radiances (public release)
  • WRF-NMM interface
  • global ARW interface
  • Multi-variate humidity analysis
  • Hybrid Var/ETKF (tutorial and monthly experiment)
  • Outerloop and QC
  • Forecast sensitivity to observations
  • Future plan and summary

3
WRF-Var in the WRF Modeling System
4
WRF-Var (WRFDA) Data Assimilation Overview
  • Goal Community WRF DA system for
  • regional/global,
  • research/operations, and
  • deterministic/probabilistic applications.
  • Techniques
  • 3D-Var
  • 4D-Var (regional)
  • Ensemble DA,
  • Hybrid Variational/Ensemble DA.
  • Model WRF (ARW, NMM, Global)
  • Support
  • NCAR/ESSL/MMM/DAG
  • NCAR/RAL/JNT/DATC
  • Observations Conv.Sat.Radar

5
WRF-Var Observations
  • In-Situ
  • Surface (SYNOP, METAR, SHIP, BUOY).
  • Upper air (TEMP, PIBAL, AIREP, ACARS).
  • Remotely sensed retrievals
  • Atmospheric Motion Vectors (geo/polar).
  • Ground-based GPS Total Precipitable Water.
  • SSM/I oceanic surface wind speed and TPW.
  • Scatterometer oceanic surface winds.
  • Wind Profiler.
  • Radar radial velocities and reflectivities.
  • Satellite temperature/humidities.
  • GPS refractivity (e.g. COSMIC).
  • Radiative Transfer
  • RTTOVS (EUMETSAT).
  • CRTM (JCSDA).

6
WRF-Var tutorials
  • 21-22 July, 2008. NCAR.
  • 2-4 Feb, 2009. NCAR.
  • 17-24 Feb, 2009. Kunming, Yunnan, China.
  • 18 April, 2009. South Korea.
  • 20-22 July, 2009
  • September 2009. UK.
  • WRF-Var tutorial agenda and presentations
  • http//www.mmm.ucar.edu/wrf/users/wrfda/tutorial.h
    tml
  • WRF-Var online tutorial and user guide
  • http//www.mmm.ucar.edu/wrf/users/wrfda/Docs/user_
    guide_V3.1/users_guide_chap6.htm
  • WRFDA
  • http//www.mmm.ucar.edu/wrf/users/wrfda

7
WRF 4D-Var Summary
  • 4D-Var included within WRF-Var.
  • Linear/adjoint models based on WRF-ARW.
  • Status
  • Parallel code, JcDFI, limited physics.
  • Delivered to AFWA in 2006 and 2007. (2008)
  • Current focus PBL/microphysics, optimization.
  • Advantages of 4D-Var
  • Flow-dependent response to obs
  • Better treatment of cloud/precip obs
  • Forecast model as a constraint
  • Obs at obs-times

8
WRF-Var Radiance Assimilation StatusLiu and
Auligne
  • BUFR 1b radiance ingest.
  • RTM interface RTTOV or CRTM
  • NESDIS microwave surface emissivity model
  • Range of monitoring diagnostics.
  • Quality Control for HIRS, AMSU, AIRS, SSMI/S.
  • Bias Correction (Adaptive, Variational in 2008)
  • Variational observation error tuning
  • Parallel MPI
  • Flexible design to easily add new satellite
    sensors

NOAA (HIRS, AMSU)
Aqua (AMSU, AIRS)
DMSP(SSMI/S)
9
WRF-Var and NMM (Pattanayak and Rizvi)Analysis
increments
10
Global WRF-Var (Rizvi and Duda)Analysis
increments
11
Multivariate humidity analysis
  • New analysis control variables are
  • Stream function
  • Unbalanced part of velocity potential
  • Unbalanced part of Temperature
  • Unbalanced part of pseudo relative humidity
  • Unbalanced part of surface pressure

Single observation response (1 g/Kg Moisture
innovation)
T8 45 Km Domain 104x94x57
Old
New
12
Deterministic Cycling NWP System
Forecast
Assimilation
3/4D-Var
13
Cycling WRF/WRF-Var/ETKF System
Forecast
Assimilation
E T K F
. . .
. . .
. . .
. . .
. . .
. . .
3/4D-Var
14
Cycling WRF/WRF-Var/ETKF System (Hybrid DA)
Forecast
Assimilation
E T K F
. . .
. . .
. . .
. . .
. . .
. . .
3/4D-Var
15
Analyses against Sonde observations
24 forecasts against Sonde observations
U RMSE
V RMSE
U RMSE
V RMSE
T RMSE
q RMSE
T RMSE
q RMSE
Hybrid Hybrid_mod Hybrid_modQC_ENS
3DVAR
Hybrid 3DVAR
From Meral Demirtas
16
3D-Var (4D-Var replace H by HM)
The incremental formulation (in the general form,
!)
The first outer-loop xg xb
Outer-loop d (and QC, etc)
nonlinear! Inner-loop minimization update xg
17
Investigate impact on observation rejection
algorithm due to multiple outer-loops.
  • Rejected Observation locations and number

The obs. rejection can be monitored either in
tabular form graphical form.
18
Simply Math
Linear assumption
Analysis
Forecast error
Forecast error sensitivity to initial state
Forecast error sensitivity to observations
19
Adjoint sensitivity (Thomas Auligne)
Analysis (xa)
Observation (y)
Forecast (xf)
WRF-VAR Data Assimilation
WRF-ARW Forecast Model
Define Forecast Accuracy
Background (xb)
Forecast Accuracy (F)
Observation Impact lty-H(xb)gt (?F/ ?y)
Gradient of F (?F/ ?xf)
Observation Sensitivity (?F/ ?y)
Analysis Sensitivity (?F/ ?xa)
Adjoint of WRF-ARW Forecast TL Model (WRF)
Adjoint of WRF-VAR Data Assimilation
Derive Forecast Accuracy
Background Sensitivity (?F/ ?xb)
Obs Error Sensitivity (?F/ ?eob)
Bias Correction Sensitivity (?F/ ??k)
20
Observation Impact Conventional Data
21
Observation Impact Satellite radiances
22
Observation Impact Conventional Data
23
Future Plans
  • General Goals
  • Unified, multi-technique WRF DA system.
  • Retain flexibility for research,
    multi-applications.
  • Leverage international WRF community efforts.
  • WRF-Var Development (MMM Division)
  • 4D-Var (additional physics, optimization).
  • Sensitivities tools (adjoint, ensemble, etc.).
  • EnKF within WRF-Var -gt WRFDA.
  • Instrument-specific radiance QC, bias correction,
    etc.
  • Data Assimilation Testbed Center (DATC)
  • Technique inter-comparison 3/4D-Var, EnKF,
    Hybrid
  • Obs. impact AIRS, TMI, SSMI/S, METOP.
  • New Regional testbeds US, India, Arctic,
    Tropics.
  • Applications
  • Hurricanes/Typhoons
  • OSEs and OSSEs
  • Reanalysis (Arctic System Reanalysis)
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